"The most important step of all is the first step. Start Something."

And to start your journey, below are some of the best free resources for different technologies.

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#100DaysOfCode

🧵 👇
For learning Python a few of my favorite websites:

By Google (only for python2 though):
developers.google.com/edu/python

Guided Course:
sololearn.com/learning/1073
(^ has many other guided courses too)

For Python and its applications:
automatetheboringstuff.com
inventwithpython.com/invent4thed/
For AI basics:

Guided Course: udacity.com/course/intro-t…

Just Videos by MIT: ocw.mit.edu/courses/electr…

Book/Reading Material:
Part I: course.elementsofai.com
Part II: buildingai.elementsofai.com
(^two of my favorites)

Checkout CSE courses on NPTEL:
nptel.ac.in/course.html

#AI
For Machine Learning:

By Google: developers.google.com/machine-learni…

Free Course: udacity.com/course/intro-t…

Stanford Course: see.stanford.edu/course/cs229

Topic Wise: mlcourse.ai

Book: ciml.info

Advanced Topics:
course18.fast.ai/ml.html

#MachineLearning
Deep Learning

Videos: youtube.com/playlist?list=…

(^You can check out other playlists too on sentex youtube)

Book: deeplearningbook.org

Single Video:

(^Awesome video by @simplilearn )

Project-based: neuralnetworksanddeeplearning.com

(^By @michael_nielsen)
TensorFlow:

Video:

Book: Apart from official documentation, a great book to check out is by manning publication
livebook.manning.com/book/machine-l…

Web Scrapping:
dataquest.io/blog/web-scrap…

Matplotlib:
blog.quantinsti.com/python-matplot…

R Programming:
r4ds.had.co.nz/index.html
Let us know what topic you are learning so that we can help you with free resources on that.

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More from @PythonLover9

7 Apr
Let's learn about Correlation the most important statistical measure that is also a key tool in machine learning.

#MachineLearning #100DaysOfCode #Python

👇🧵
Correlation, as the name suggests, gives the measure of the relationship between two variables.

In statistical terms, it is the measure using which statisticians figure out how much two things are related.

Two things could be related in different extend and ways. For eg:
1) If one variable increases, the other variable might increase(+ve correlation), decreases(-ve correlation) or remain unchanged/have no defined pattern( uncorrelated ).

2) Also, this behavior could remain the same for all the values(monotonic) or can vary with the values. ImageImageImage
Read 13 tweets

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